Table 1.

Lean/obese clinical trials.

Study identification	Description	N	Population description	Outcomes
Kasai et al. 2015 [22]	Cross-sectional study	56 (10)	Japanese population: 23 BMI < 20 kg/m2 and 33 BMI ≥ 25 kg/m2 Subsample: 4 nonobese and 6 obese subjects	Bacterial diversity was significantly greater in obese subjects compared with nonobese subjects. Reduced numbers of Bacteroidetes and a higher F/B ratio in obese subjects compared with nonobese subjects.
	Microbiota fecal samples
	16S DNA sequencing Metagenome@KIN software
	Corresponding OTU identified according to T-RFLP
Million et al. 2012 [23]	Cross-sectional study	115	68 obese and 47 controls	L. reuteri was associated with obesity. M. smithii was depleted in obese subjects. Some Bifidobacterium or Lactobacillus species were associated with normal weight (B. animalis).
	Microbiota fecal samples
	qPCR targeting Firmicutes, Bacteroidetes, Lactococcus lactis, Methanobrevibacter smithii, and Bifidobacterium animalis
Haro et al. 2016 [24]	Cross-sectional study	75	39 men and 36 women with CVD within CORDIOPREV study 3 groups according to BMI: BMI < 30, 30 < BMI < 33, and BMI > 33	F/B ratio changed with the BMI and between genders. Men had higher F/B ratio under a BMI of 33. By contrast, men had a significantly lower F/B ratio than women in the BMI > 33 group. At genera level, BMI > 33: higher Bacteroides genus in women, but decrease in men.
	Baseline fecal samples
	16S rRNA sequencing
	QIIME software
Lin et al. 2015 [25]	Cross-sectional study	659	Healthy Chinese adults Asian: normal BMI < 23 (N = 281), overweight 23-<27.5 (N = 304), and obese > 27.5 (N = 55)	BMI was not associated with the bacterial community diversity as assessed by alpha diversity in the models.
	Upper gastrointestinal microbial diversity
	16S rRNA sequencing
	HOMIM software
Angelakis et al. 2015 [26]	Cross-sectional study	10	5 lean subjects: BMI 20.7 5 obese subjects: BMI 36.8	Firmicutes and Actinobacteria were the most predominant phyla of the bacterial composition of the duodenal microbiota in both groups. The obese group presented a higher proportion of anaerobic genera and a lesser proportion of aerobic genera, mostly associated with the presence of Veillonella, Bulleidia, and Oribacterium.
	Duodenal microbiota
	16S rDNA sequencing
	Illumina MiSeq
Finucane et al. 2014 [27]	Review of 4 different studies Human Microbiome Project (HMP) and MetaHIT	159	HMP project: 24 obese (BMI > 30) and 123 lean (BMI < 25) individuals MetaHIT project: Danish MetaHIT cohort included 12 individuals (BMI > 35)	The interstudy variability in the taxonomic composition of stool microbiomes far exceeds differences between lean and obese individuals within studies. No quantitative association between the continuous BMI variable and the ratio of B/F. Variation in the relative abundance of F and B is much larger among studies than between lean and obese individuals within any study. MetaHIT and HMP go in the opposite direction [11].
Goodrich et al. 2014 [30]	Cross-sectional study	977	Twin population: 416 twin pairs, mostly females, mean age 60.6 ± 0.3 years N = 433: BMI < 25 N = 322: BMI 25–30 N = 183: BMI > 30	The family Christensenellaceae was significantly enriched in subjects with a BMI < 25 compared to those with BMI > 30. Overall, a majority (n = 35) of the OTUs with highest heritability scores were enriched in the lean subjects. A subset of OTUs classified as Oscillospira were enriched in lean subjects, and M. smithii, though not significantly heritable, was positively associated with a lean BMI.
	Fecal samples from the twins UK population
	16S rRNA
	Illumina MiSeq
	QIIME software
Bondia-Pons et al. [35]	Cross-sectional study	50	16 healthy monozygotic twin pairs discordant for weight (BMI difference > 3 kg/m2) Control pairs: nine concordant monozygotic pairs	No differences in fecal bacterial diversity were detected when comparing cotwins discordant for weight. We found that within-pair similarity is a dominant factor in the metabolic postprandial response, independent of acquired obesity.
	Fecal samples
	Diversity of the major bacterial groups by using 5 different validated bacterial group-specific DGGE methods
Murugesan et al. [31]	Cross-sectional study	190	190 unrelated Mexican children 9–11 years old 81 normal 29 overweight 80 obese	No statistical significant differences in abundance of phylum.
Ignacio et al. [32]	Cross-sectional study	84	30 obese, 24 overweight, and 30 lean children (3–11 years old)	B. fragilis group and Lactobacillus spp. were found at high concentrations in obese and overweight children when compared with the lean ones and positively correlated with BMI. Bifidobacterium spp. were found in higher numbers in the lean group than the overweight and obese ones. Furthermore, a negative correlation between BMI and Bifidobacterium spp. copy number was observed.
Hu et al. [33]	Cross-sectional study fecal samples from 67 obese (BMI > 30 kg/m2) and 67 normal (BMI < 25 kg/m2) individuals	134	Korean adolescents aged 13–16 years	No significant differences in the Bacteroidetes, Firmicutes, and Proteobacteria populations in samples from normal and obese adolescents at the phylum level, although the proportion of Bacteroides was highest in normal children (45%), whereas that in obese was 25%. Conversely, the proportion of Prevotella in BMI < 25 was 16%; obese adolescents (35%).

T-RFLP reference human fecal microbiota profiling; qPCR: quantitative PCR; CVD: cardiovascular disease; DGGE: denaturing gradient gel electrophoresis.